code: def get_initial_state(self):
      policy_initial_state = self.action_model.get_initial_state()
      q_initial_state = self.q_net.get_initial_state()
      if self.twin_q_net:
          q_initial_state *= 2
      return policy_initial_state + q_initial_state
  
file_path: ray/rllib/algorithms/sac/rnnsac_torch_model.py
imports: import gymnasium
  from typing import Optional, List, Dict
  from ray.rllib.algorithms.sac.sac_torch_model import SACTorchModel
  from ray.rllib.models.modelv2 import ModelV2
  from ray.rllib.policy.sample_batch import SampleBatch
  from ray.rllib.policy.view_requirement import ViewRequirement
  from ray.rllib.utils import override, force_list
  from ray.rllib.utils.framework import try_import_torch
  from ray.rllib.utils.typing import ModelConfigDict, TensorType
label_desc: Use image node_id 6 for calling the RNNSACTorchModel obj's underlying member method code with example usage: obj.get_initial_state() and returns: unknown